An Effective Technique to Track Objects with the Aid of Rough Set Theory and Evolutionary Programming

2019 ◽  
Vol 28 (1) ◽  
pp. 1-13
Author(s):  
Kumaraperumal Shanmugapriya ◽  
RajaMani Suja Mani Malar
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Texture Feature ◽  
Evolutionary Programming ◽  
Computing Technique ◽  
Monitoring Process ◽  
Effective Manner ◽  
Wide Range ◽  
The Impact

AbstractDue to its wide range of applications, the impact of multimedia in the real world has shown stupendous growth. Texts, images, audio, and video are the different forms of multimedia which are utilized by humans in various applications such as education and surveillance applications. A wide range of research has been carried out, and here in this paper, we propose an object racking with the aid of rough set theory in combination with the eminent soft computing technique evolutionary programming. Initially, the input video is segregated into frames, then the frames that belong to particular shots are identified through the shot segmentation process, and after that the object to be tracked is identified manually. Subsequently, the shape and texture feature is extracted, and then the rough set theory is applied. This is done to identify the presence of object in the frames. Consequently, genetic algorithm (GA) is utilized for the object monitoring process to mark the object with variant color. As a result, the selected object is tracked in an effective manner.

Rough Set Classification Algorithms Based on Texture Feature

2013 ◽  
Vol 347-350 ◽  
pp. 3119-3122
Author(s):  
Yan Xue Dong ◽  
Fu Hai Huang
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Texture Classification ◽  
Texture Feature ◽  
Decision Table ◽  
Classification Algorithms ◽  
Reduction Algorithm ◽  
Discrete Method ◽  
Knowledge Reduction

The basic theory of rough set is given and a method for texture classification is proposed. According to the GCLM theory, texture feature is extracted and generate 32 feature vectors to form a decision table, find a minimum set of rules for classification after attribute discretization and knowledge reduction, experimental results show that using rough set theory in texture classification, accompanied by appropriate discrete method and reduction algorithm can get better classification results

scholarly journals Boosting Accuracy of Classical Machine Learning Antispam Classifiers in Real Scenarios by Applying Rough Set Theory

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
N. Pérez-Díaz ◽  
D. Ruano-Ordás ◽  
F. Fdez-Riverola ◽  
J. R. Méndez
Keyword(s):  
Machine Learning ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Support Vector ◽  
Wide Range ◽  
Vector Machines ◽  
Bayes Algorithm

Nowadays, spam deliveries represent a major problem to benefit from the wide range of Internet-based communication forms. Despite the existence of different well-known intelligent techniques for fighting spam, only some specific implementations of Naïve Bayes algorithm are finally used in real environments for performance reasons. As long as some of these algorithms suffer from a large number of false positive errors, in this work we propose a rough set postprocessing approach able to significantly improve their accuracy. In order to demonstrate the advantages of the proposed method, we carried out a straightforward study based on a publicly available standard corpus (SpamAssassin), which compares the performance of previously successful well-known antispam classifiers (i.e., Support Vector Machines, AdaBoost, Flexible Bayes, and Naïve Bayes) with and without the application of our developed technique. Results clearly evidence the suitability of our rough set postprocessing approach for increasing the accuracy of previous successful antispam classifiers when working in real scenarios.

scholarly journals APPLYING ROUGH SET THEORY TO GENETIC ALGORITHM FOR WEB SERVICE COMPOSITION

2014 ◽  
pp. 268-273
Author(s):  
CARIAPPA M.M ◽  
MYDHILI .K. NAIR
Keyword(s):  
Genetic Algorithm ◽  
Web Services ◽  
Set Theory ◽  
Rough Set ◽  
Input Data ◽  
Business Processes ◽  
Rough Set Theory ◽  
Initial Population ◽  
Computing Technique ◽  
Imperfect Data

Rough set theory is a very efficient tool for imperfect data analysis, especially to resolve ambiguities, classify raw data and generate rules based on the input data. It can be applied to multiple domains such as banking, medicine etc., wherever it is essential to make decisions dynamically and generate appropriate rules. In this paper, we have focused on the travel and tourism domain, specifically, Web-based applications, whose business processes are run by Web Services. At present, the trend is towards deploying business processes as composed web services, thereby providing value-added services to the application developers, who consumes these composed services. In this paper, we have used Genetic Algorithm (GA), an evolutionary computing technique, for composing web services. GA suffers from the innate problem of larger execution time when the initial population (input data) is high, as well as lower hit rate (success rate). In this paper, we present implementation results of a new technique of solving this problem by applying two key concepts of rough set theory, namely, lower and upper approximation and equivalence class to generate if-then decision support rules, which will restrict the initial population of web services given to the genetic algorithm for composition.

A rough set theory application in forecasting models

2020 ◽  
Vol 3 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Haresh Sharma ◽  
◽  
Kriti Kumari ◽  
Samarjit Kar ◽  
◽  
...  
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Forecasting Models ◽  
Theory Application

Extraction of Geo-spatial Relationship Rules Based on Rough Set Theory: Exemplified by Land Use

2009 ◽  
Vol 11 (2) ◽  
pp. 139-144
Author(s):  
Feng CAO ◽  
Yunyan DU ◽  
Yong GE ◽  
Deyu LI ◽  
Wei WEN
Keyword(s):  
Land Use ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Spatial Relationship
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